Occupational disease diagnostician (ODD) is the core technology professional who is responsible for occupational disease diagnosis and identification and the main inspection work for occupational medical examination. The implementation of regular assessment management for ODDs is a key component of standardized workforce management, which facilitates dynamic evaluation of professional competence, regulation of medical practice, and assurance of medical safety. Since January 2025, Guangdong Province has implemented regular assessment management for ODDs within its administrative region. The assessment adopts an integrated model consisting of three components including professional competency evaluation, performance appraisal, and professional ethics evaluation, with each assessment cycle lasting three years. ODDs who passed all three components are classified as qualified ODD, whereas those who failed to pass any one of the three components result in an unqualified assessment outcome. In the implementation of ODD regular assessment management, Guangdong Province has emphasized integrating assessment with quality evaluation, strengthening full-cycle supervision of ODDs′ professional conduct, optimizing assessment strategies for special groups of ODDs, and reinforcing the primary management responsibility of medical institutions. Meanwhile, ODDs′ professional competence, service quality, and professional integrity have been continuously promoted by adopting human-computer interactive assessments, information-based assessment management, and "elimination" mechanism.

OBJECTIVES: To explore the risk factors of feeding intolerance (FI) in critically ill children receiving enteral nutrition (EN) and to construct a prediction nomogram model for FI. METHODS: A retrospective study was conducted to collect data from critically ill children admitted to the Pediatric Intensive Care Unit of Xiangya Hospital, Central South University, between January 2015 and October 2020. The children were randomly divided into a training set (346 cases) and a validation set (147 cases). The training set was further divided into a tolerance group (216 cases) and an intolerance group (130 cases). Multivariate logistic regression analysis was used to screen for risk factors for FI in critically ill children receiving EN. A nomogram was constructed using R language, which was then validated on the validation set. The model's discrimination, calibration, and clinical net benefit were evaluated using receiver operating characteristic curves, calibration curves, and decision curves. RESULTS: Duration of bed rest, shock, gastrointestinal decompression, use of non-steroidal anti-inflammatory drugs, and combined parenteral nutrition were identified as independent risk factors for FI in critically ill children receiving EN (P<0.05). Based on these factors, a nomogram prediction model for FI in critically ill children receiving EN was developed. The area under the receiver operating characteristic curve for the training set and validation set was 0.934 (95%CI: 0.906-0.963) and 0.852 (95%CI: 0.787-0.917), respectively, indicating good discrimination of the model. The Hosmer-Lemeshow goodness-of-fit test showed that the model had a good fit (χ 2=12.559, P=0.128). Calibration curve and decision curve analyses suggested that the model has high predictive efficacy and clinical application value. CONCLUSIONS Duration of bed rest, shock, gastrointestinal decompression, use of non-steroidal anti-inflammatory drugs, and combined parenteral nutrition are independent risk factors for FI in critically ill children receiving EN. The nomogram model developed based on these factors exhibits high predictive efficacy and clinical application value.
Humans ; Critical Illness ; Enteral Nutrition/adverse effects* ; Male ; Risk Factors ; Female ; Child, Preschool ; Infant ; Nomograms ; Retrospective Studies ; Child ; Logistic Models

Postoperative infection of internal fixation of closed fractures the lower limbs in adults represents a devastating complication, characterized by diagnostic challenges, prolonged treatment duration and high disability rates. Current management of these infections faces multiple challenges, such as difficulties in early accurate diagnosis, and various controversies about the treatment plan, leading to poor overall diagnosis and treatment results. To address these issues, based on evidence-based medicine and principles with emphasis on scientific rigor, clinical applicability and innovation, the Trauma Branch of the Chinese Medical Association, Orthopedic Branch of the Chinese Medical Doctor Association, Orthopedics Branch of the Chinese Medical Association, and Trauma Orthopedics and Polytrauma Group of the Resuscitation and Emergency Committee of the Chinese Medical Doctor Association have collaboratively organized a panel of relevant experts to develop the Guideline for diagnosis and treatment of infection after internal fixation of closed lower limb fractures in adults ( version 2025). The guideline proposed 10 recommendations, aiming to provide a foundation for standardized diagnosis and treatment of postoperative infection in adults with closed lower limb fractures.

This consensus was developed by the Orthodontic Society of the Chinese Stomatological Association to provide a systematic, scientific, and practical guideline for informed consent in orthodontic care. Orthodontic treatment is typically lengthy, highly individualized, and involves multiple factors such as growth and development, occlusal function, and facial esthetics. Rapid technological advances and diverse risk profiles make the traditional reliance on orthodontist experience or institutional templates insufficient to ensure patients′ full understanding and autonomous decision-making. To address this, the expert panel conducted extensive reviews of domestic and international guidelines, analyzed representative dispute cases, and performed multicenter patient-clinician surveys. Using a multi-round Delphi method, the group established a standardized informed consent framework covering the initial consultation, treatment, and retention phases. The consensus emphasizes that informed consent is not only a fundamental legal and ethical requirement but also a key step in building trust, improving patient compliance, and enhancing treatment satisfaction. Orthodontists should clearly and comprehensively explain treatment plans, potential risks, uncertainties, and associated costs, while respecting the autonomy of patients or guardians, and maintain continuous communication and dynamic evaluation throughout the treatment process. The release of this consensus provides unified and authoritative guidance for clinical orthodontics, helping to standardize informed consent, enhance its transparency, safeguard patient rights, reduce medical risks, and promote high-quality, sustainable development of orthodontic practice.

Enamel demineralization, the formation of white spot lesions, is a common issue in clinical orthodontic treatment. The appearance of white spot lesions not only affects the texture and health of dental hard tissues but also impacts the health and aesthetics of teeth after orthodontic treatment. The prevention, diagnosis, and treatment of white spot lesions that occur throughout the orthodontic treatment process involve multiple dental specialties. This expert consensus will focus on providing guiding opinions on the management and prevention of white spot lesions during orthodontic treatment, advocating for proactive prevention, early detection, timely treatment, scientific follow-up, and multidisciplinary management of white spot lesions throughout the orthodontic process, thereby maintaining the dental health of patients during orthodontic treatment.
Humans ; Consensus ; Dental Caries/etiology* ; Dental Enamel/pathology* ; Tooth Demineralization/etiology* ; Tooth Remineralization

Early correction of childhood malocclusion is timely managing morphological, structural, and functional abnormalities at different dentomaxillofacial developmental stages. The selection of appropriate imaging examination and comprehensive radiological diagnosis and analysis play an important role in early correction of childhood malocclusion. This expert consensus is a collaborative effort by multidisciplinary experts in dentistry across the nation based on the current clinical evidence, aiming to provide general guidance on appropriate imaging examination selection, comprehensive and accurate imaging assessment for early orthodontic treatment patients.
Humans ; Malocclusion/diagnostic imaging* ; Child ; Consensus

Objective To investigate the expression of SORT1 in the gastric cancer tissue and analyze its relationship with clinical prognosis of patients as well as the pathways and mechanisms involved in gastric cancer progression.Methods The Gene Expression Profiling Interaction Analysis database,Western blot,and immunohistochemistry were employed to predict and analyze the expression of SORT1 in the gastric cancer and the adjacent tissue.The clinical case information of 109 patients who underwent radical surgery for gastric cancer in the First Affiliated Hospital of Bengbu Medical University from April 2015 to April 2017 was collected to analyze the relationship of SORT1 with the clinicopathological parameters and prognosis of the patients.Cell proliferation was detected by the CCK-8 assay and colony formation assay,while cell migration and invasion were assessed by the scratch assay and Transwell assay,respectively.Western blot was employed to determine the expression of proteins related to epithelial-mesenchymal transition(EMT)in gastric cancer cells,followed by further analysis on molecular mechanism through which SORT1 regulates EMT in gastric cancer cells.Results Western blot and immunocytochemistry results showed that SORT1 was highly expressed in the gastric cancer tissue(P=0.003,P<0.001),which was positively correlated with malignant progression of tumors(all P<0.05).The Kaplan-Meier survival analysis revealed shortened postoperative survival periods for the patients with high expression of SORT1(P<0.001).The Cox regression model indicated that SORT1 expression was an independent risk factor affecting the 5-year survival rate after surgery for gastric cancer patients(P<0.001).Up-regulation of SORT1 expression promoted the proliferation,migration,invasion,and EMT of gastric cancer cells(all P<0.05),while down-regulation of SORT1 showed the opposite effects(all P<0.05).Western blot results showed that high expression of SORT1 promoted the expression of β-catenin,cyclin D1,and c-Myc(all P<0.05).Moreover,in vitro use of the Wnt/β-catenin pathway inhibitor(XAV939)effectively suppressed the EMT enhancement caused by high expression of SORT1 in gastric cancer cells(all P<0.05).Conclusions SORT1 is highly expressed in gastric cancer and affects patients' postoperative survival periods.It is involved in the proliferation,migration,and invasion of gastric cancer cells and may promote the EMT of gastric cancer cells by activating the Wnt/β-catenin pathway.
Humans ; Stomach Neoplasms/pathology* ; Cell Proliferation ; Epithelial-Mesenchymal Transition ; Cell Movement ; Prognosis ; Cell Line, Tumor ; Adaptor Proteins, Vesicular Transport/metabolism* ; Male ; Female ; Middle Aged

Objective To explore the nephrotoxic effects of exposure to perfluorobutanoic acid (PFBA) and its mechanism in mice, with a particular focus on analyzing the changes in kidney metabolism and their potential implications. Methods The specific pathogen free C57BL/6 mice were randomly divided into control group, low-dose group, and high-dose group, with 10 mice in each group. Mice in the three groups received intragastric administration of PFBA solution at doses of 0, 35 and 350 mg/kg body weight, once per day for seven consecutive days. The histopathological changes of kidneys of mice in these three groups were evaluated. Metabolomic profiling of mouse kidneys was performed using ultra-high-performance liquid chromatography coupled with quadrupole time-of-flight mass spectrometry. Differentially accumulated metabolites (DAMs) were identified based on the Human Metabolome Database, and related metabolic pathways were analyzed through MetaboAnalyst 6.0 and Kyoto Encyclopedia of Genes and Genomes (KEGG). Results Histopathological analysis of kidneys showed that the renal pelvis mucosa of mice in the low-dose group presented focal mild inflammatory changes without marked structural damage, whereas mice in the high-dose group showed severe inflammation and partial destruction of renal structure. The kidney coefficient of mice in both low-dose group and the high-dose group decreased (both P<0.05), and the Paller scores of renal tissues increased (both P<0.05) compared with that in the control group. The Paller score of mouse renal tissue in the high-dose group was higher than that in the low-dose group (P<0.05). Metabolomic profiling identified 46 DAMs (26 upregulated, 20 downregulated) in the low-dose group and 104 DAMs (54 upregulated, 50 downregulated) in the high-dose group, with 26 shared DAMs between the two dose groups. KEGG pathway analysis revealed that DAMs were mainly involved in metabolic pathways such as glycerophospholipid metabolism, glycerolipid metabolism, sphingolipid and steroid hormone synthesis. Conclusion Acute exposure to PFBA can cause kidney injury in mice. Lipid metabolism pathways such as glycerophospholipid and sphingolipid metabolism is involved in the development of acute renal toxicity of PFBA.

Alzheimer’s disease (AD) is a chronic neurodegenerative disorder that severely affects the health of the elderly, marked by its incurability, high prevalence, and extended latency period. The current approach to AD prevention and treatment emphasizes early detection and intervention, particularly during the pre-AD stage of mild cognitive impairment (MCI), which provides an optimal “window of opportunity” for intervention. Clinical detection methods for MCI, such as cerebrospinal fluid monitoring, genetic testing, and imaging diagnostics, are invasive and costly, limiting their broad clinical application. Speech, as a vital cognitive output, offers a new perspective and tool for computer-assisted analysis and screening of cognitive decline. This is because elderly individuals with cognitive decline exhibit distinct characteristics in semantic and audio information, such as reduced lexical richness, decreased speech coherence and conciseness, and declines in speech rate, voice rhythm, and hesitation rates. The objective presence of these semantic and audio characteristics lays the groundwork for computer-based screening of cognitive decline. Speech information is primarily sourced from databases or collected through tasks involving spontaneous speech, semantic fluency, and reading, followed by analysis using computer models. Spontaneous language tasks include dialogues/interviews, event descriptions, narrative recall, and picture descriptions. Semantic fluency tasks assess controlled retrieval of vocabulary items, requiring participants to extract information at the word level during lexical search. Reading tasks involve participants reading a passage aloud. Summarizing past research, the speech characteristics of the elderly can be divided into two major categories: semantic information and audio information. Semantic information focuses on the meaning of speech across different tasks, highlighting differences in vocabulary and text content in cognitive impairment. Overall, discourse pragmatic disorders in AD can be studied along three dimensions: cohesion, coherence, and conciseness. Cohesion mainly examines the use of vocabulary by participants, with a reduction in the use of nouns, pronouns, verbs, and adjectives in AD patients. Coherence assesses the ability of participants to maintain topics, with a decrease in the number of subordinate clauses in AD patients. Conciseness evaluates the information density of participants, with AD patients producing shorter texts with less information compared to normal elderly individuals. Audio information focuses on acoustic features that are difficult for the human ear to detect. There is a significant degradation in temporal parameters in the later stages of cognitive impairment; AD patients require more time to read the same paragraph, have longer vocalization times, and produce more pauses or silent parts in their spontaneous speech signals compared to normal individuals. Researchers have extracted audio and speech features, developing independent systems for each set of features, achieving an accuracy rate of 82% for both, which increases to 86% when both types of features are combined, demonstrating the advantage of integrating audio and speech information. Currently, deep learning and machine learning are the main methods used for information analysis. The overall diagnostic accuracy rate for AD exceeds 80%, and the diagnostic accuracy rate for MCI also exceeds 80%, indicating significant potential. Deep learning techniques require substantial data support, necessitating future expansion of database scale and continuous algorithm upgrades to transition from laboratory research to practical product implementation.

Objective The risk prediction model of shivering during cesarean section was constructed and its prediction effect was verified.Methods A total of 225 parturient women who underwent cesarean section in the Second Affiliated Hospital of Wenzhou Medical University from January to April 2023 were selected as study objects.According to whether shivering occurred during the operation,they were divided into shivering group(101 cases)and non-shivering group(124 cases).Multivariate Logistic regression was used to analyze the influencing factors and build a nomogram prediction model.Results The parity and proportion of intraoperative warming measures in shivering group were significantly lower than those in non-shivering group,and the proportion of diabetes,globulin,state anxiety inventory(S-AI)score and trait anxiety inventory score were significantly higher than those in non-shivering group,and post-anesthesia body temperature decrease was significantly greater than that in non-shivering group(P＜0.05).Multivariate Logistic regression analysis revealed that diabetes history,S-AI score,anesthesia method,post-anesthesia body temperature decrease,and intraoperative warming measures were all influencing factors of shivering during cesarean section(P＜0.05).The area under the curve(AUC)of the constructed prediction model for predicting shivering during cesarean section was 0.831,and the maximum AUC obtained by ten-fold internal cross-validation was 0.934,suggesting that the model had good fitting effect and differential validity.Conclusion The model can predict the risk of parturient shivering during cesarean section,and provide reference for medical personnel to take preventive management measures for high-risk puerperal shivering in time.